Knowledge Discovery in the Social Sciences : A Data Mining Approach
- Author/Creator:
- Shu, Xiaoling, 1968- author
- Publication/Creation:
- Berkeley, CA : University of California Press, [2020]
- Resource Type:
- Book
More Details
Additional/Related Title Information
- Full Title:
- Knowledge Discovery in the Social Sciences : A Data Mining Approach / Xiaoling Shu
- Related/Included Titles:
- Frontmatter --
CONTENTS --
Chapter 1. Introduction --
Chapter 2. New Contributions and Challenges --
Chapter 3. Data Issues --
Chapter 4. Data Visualization --
Chapter 5. Assessment of Models --
Chapter 6. Cluster Analysis --
Chapter 7. Associations --
Chapter 8. Generalized Regression --
Chapter 9. Classification and Decision Trees --
Chapter 10. Artificial Neural Networks --
Chapter 11. Web Mining and Text Mining --
Chapter 12. Network or Link Analysis --
Index
Subjects/Genre
Description/Summary
- Table of Contents:
- Frontmatter -- CONTENTS -- Chapter 1. Introduction -- Chapter 2. New Contributions and Challenges -- Chapter 3. Data Issues -- Chapter 4. Data Visualization -- Chapter 5. Assessment of Models -- Chapter 6. Cluster Analysis -- Chapter 7. Associations -- Chapter 8. Generalized Regression -- Chapter 9. Classification and Decision Trees -- Chapter 10. Artificial Neural Networks -- Chapter 11. Web Mining and Text Mining -- Chapter 12. Network or Link Analysis -- Index
- Summary:
- Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries
- Language:
- English
- Language Note:
- In English.
- Physical Type/Description:
- 1 online resource (264 pages)
Additional Identifiers
- Catalog ID (MMSID):
- 9937607217302486
- ISBN:
- 0-520-96587-6
- OCLC Number:
- 1110674217
- Other Identifiers:
- doi: 10.1525/9780520965874
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